Robotics Systems Lab
A world-class field operation advancing robotic systems for air, land, sea, and space.
The RSL provides interdisciplinary, hands-on engineering education that engages and challenges undergraduate and graduate students in exciting ways. Systems are designed and controlled by students to meet the specific needs of a wide range of external clients and collaborators from government, academia, industry, and nonprofit sectors.
The Robotics Systems Laboratory was selected by the National Academy of Engineering as a model program for its Real World Engineering initiative and publication.
- Satellite mission control center with distributed radio communication stations on campus, at NASA Ames, and across the country
- Mobile mission control center
- NASA Ames Research Center lab facility
- Several underwater robots, ranging from professional-class 1000' vehicles to pool-grade vehicles
- Several autonomous boats, to include a science-grade bathymetric mapping vessel to a fleet of automated kayaks
- Automated Gator-class ATV
- More than a dozen research-grade wheeled robots
- Ten research-class aerial vehicles, ranging from octocopters to fixed wing drones
- Operational control of multiple on-orbit NASA spacecraft in the end-of-life testing and educational use phase
- Robot manipulator workcell
- Ultrawideband tracking system
- Vision tracking system
- A range of marine instrumentation to include CTD sensors, samplers, etc.
- A range of imagers for land and aerial vehicles, to include visual and infrared cameras as well as a multispectral imaging system
- Indoor drone test chamber
- Indoor 100,000 class clean tent
- SUV and pickup truck
- 7 support trailers
Affiliate Access Agreements
- Monterey Bay Aquarium Research Institute: Access to marine systems, indoor test tank, test equipment, and machine shop
- NASA Ames Research Center: Access to development labs, field test sites, etc.
Bringing fresh, delicious, nutritious food to the 1.1 billion malnourished people in the world is the mission of Sam Bertram ’16, M.S. ’18. The technical and entrepreneurial skills he developed at SCU are helping him turn his vision to reality.
RSL staff member Thomas Adamek and graduate students Michael Neumann and Jasmine Cashbaugh led a number of students in an underwater robotics deployment in Monterey Bay as part of the ENGR 180 Marine Operations course. Students learned how to deploy and pilot the Triton tethered underwater robot. Guests included Fr. John Rose Santiago and program mentor Lloyd Droppers.
Director: Dr. Chris Kitts
Santa Clara University
School of Engineering
500 El Camino Real
Santa Clara, CA 95053
Robotic Systems Laboratory students Jose Acain and Kamak Ebadi, with staff/faculty co-authors Thomas Adamek, Mike Rasay and Christopher Kitts (mechanical engineering), were awarded the Best Student Paper Award at the 2015 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications in Boston, MA. The paper, "A Multi-Robot Testbed for Adaptive Sampling Experimentation via Radio Frequency Fields," reviews the lab's use of configurable, low-power, radio broadcast networks to establish easily sampled scalar fields to provide controlled field experimentation involving the lab's novel, multi-robot adaptive navigation techniques.
Graduate students Matthew Chin and Michael Neumann, with advisor Christopher Kitts received the Best Student Paper Award at the International Conference on Intelligent Automation and Robotics for "Object Manipulation Through Explicit Force Control Using Cooperative Mobile Multi-Robot Systems."
Christopher Kitts and Mike Rasay published “A University-Based Distributed Satellite Mission Control Network for Operating Professional Space Missions,” in Acta Astronautica.
Christopher Kitts and graduate student Ashish Nair (mechanical engineering), with Nam Ling (computer engineering), received an equipment grant from nVIDIA to support a project involving the development of a novel 360-degree field of view panoramic 3D imaging and localization system. The system will exploit the GPU capabilities on nVIDIA embedded processing hardware to prototype a high-performance, low-cost robotic vision system.